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However, the second method (mean of ratio values) might yield an inappropriate outcome regarding the overall tendency of the multiplication factors.
In the case of the mean of ratio estimator (Eqs. 5.1 and 5.2), the bias correction factor of Hartley and Ross (1954) was incorporated into the estimator.
Särndal et al. (1992, Sects. 7.3, 7.4) considered this issue of hetereoscedasticity for one of the ratio estimators used here (the mean of ratio estimator see later).
It is an estimator of the slope of the model assumed here as defined by Eq. (1) with α = 0; Särndal et al. (1992, Sects. 7.3, 7.4) discussed this specifically in relation to the mean of ratio estimator.
For all genes, about 62% of the major isoforms had a ratio greater than 0.8 (Additional File 1A, the mean of ratio was 0.82, Median = 0.93, SD = 0.21).
For genes with multiple isoforms, about 40% of major isoforms had a ratio greater than 0.8 (Additional File 1B, the mean of ratio was 0.71, Median = 0.72; SD = 0.20).
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For continuous-variable approaches, means of ratios were obtained for each gene analyzed.
The denominator is long-term mean of ratios of yearly maximum temperature and EVI with exclusion of the year under consideration.
Ratios representing peak stimulation were calculated as the mean of ratios for the three highest time points between 2 and 5 min after arginine stimulation.
This factor can be obtained as the mean of ratios of intensities of corresponding bands (treatment/control) for bands originating from transcripts that are unchanged by the treatment.
For the analysis of pooled sample-based array data, we used Monte-Carlo simulations of the mean of ratios of allelic frequencies and coefficient of variation to rank the 262,000 array SNPs.
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